Principal Architect, AI/ML

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Architect, AI/ML based in the United States.

This is a senior technical leadership role at the forefront of enterprise AI transformation, where you will design and guide the implementation of advanced machine learning and generative AI systems for complex, real-world business use cases. You will act as a trusted advisor to clients, shaping architecture decisions that span model training, optimization, deployment, and large-scale production serving. The role requires deep expertise in modern AI/ML systems, combined with the ability to translate technical complexity into clear business value. You will work closely with engineering, cloud, and data teams to build secure, scalable, and privacy-conscious AI solutions. A key part of the role involves helping organizations adopt agentic systems and LLM-powered architectures in a cost-efficient and responsible way. This is a highly influential position that blends hands-on architecture, client-facing leadership, and thought leadership in a rapidly evolving AI landscape.

• Serve as the senior technical authority on AI/ML architecture, guiding the design and implementation of advanced machine learning and generative AI systems.
• Lead pre-sales and solution design efforts, partnering with business development teams to scope opportunities and present technical solutions to clients.
• Architect end-to-end AI systems, including model training, fine-tuning, optimization, deployment, and production-scale serving.
• Design secure, privacy-compliant, and data-sovereign AI solutions aligned with regulatory requirements such as GDPR.
• Guide the selection and application of cloud-native technologies, with emphasis on Google Cloud and large-scale AI infrastructure.
• Lead the design of agentic systems and workflows using modern frameworks such as LangGraph, LangChain, and similar tooling.
• Optimize model performance and cost efficiency through techniques such as quantization, pruning, and advanced serving strategies.
• Collaborate with cloud and data architects to ensure cohesive, scalable end-to-end solutions for enterprise clients.
• Provide technical mentorship to internal teams and clients, establishing best practices in high-performance AI engineering.
• Act as a thought leader through external contributions such as technical writing, presentations, and industry engagement.

Requirements:

• Master’s degree in Computer Science, Mathematics, Engineering, or a related technical field, or equivalent practical experience.
• Extensive experience in senior or principal architecture roles delivering production-grade AI/ML systems at scale.
• Strong hands-on experience with at least one major cloud platform (Google Cloud strongly preferred; AWS or Azure acceptable).
• Deep expertise in LLM optimization techniques including fine-tuning (e.g., LoRA), quantization, and efficient inference (e.g., vLLM, TensorRT-LLM).
• Experience with modern ML frameworks such as PyTorch, JAX, or PyTorch/XLA for training and deployment.
• Proven ability to design and implement agentic AI systems using frameworks like LangChain, LangGraph, or similar tools.
• Strong understanding of secure, private, and data-sovereign AI architecture patterns.
• Familiarity with observability and evaluation tools for LLM systems (e.g., LangSmith, Langfuse, Vertex AI Evaluation).
• Excellent communication and stakeholder management skills, with the ability to translate technical depth into business impact.
• Passion for mentoring, innovation, and staying at the forefront of AI/ML advancements.

Benefits:

• Competitive compensation aligned with senior principal-level AI/ML architecture roles.
• Fully remote work environment within the United States.
• Opportunity to lead cutting-edge AI transformation projects for enterprise clients.
• High-impact role with significant technical ownership and client influence.
• Exposure to advanced AI systems, including LLMs, agentic frameworks, and hyperscaler cloud platforms.
• Strong emphasis on professional growth, thought leadership, and technical excellence.
• Inclusive and collaborative culture supporting continuous learning and innovation.